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How Leaders Can Navigate the Internet of Things in the Workplace

By Evan Sinar, Ph.D.

Evan Sinar, Ph.D. The Internet of Things (IoT) describes a vastly-expanded state of connectivity where devices transmit status information on their own, without any human intervention. Here is a visualization that nicely illustrates the concept, and here is an executive overview. If you have a Nest Thermostat or have strapped on a FitBit, you’re already using IoT yourself. But current technologies are just the beginning and corporate applications—for tracking everything from a building’s structural integrity to the minute-by-minute fuel usage of each truck in a delivery fleet—are surging. Within five years, it’s projected that more than 50 billion devices will be connected to the Internet, and many companies are aggressively pursuing IoT to take advantage of its vast potential for improving their amount and value of data about business operations.

Internet of Things

Even though IoT is expressly designed not to rely on data entered directly by employees, it’s becoming a prevalent and influential source of data about employees—research shows adoption rates nearing 50 percent of organizations within two years for many employee-focused uses of IoT. Many IoT applications already monitor, track, and report on employee activity, productivity, and even health. However, these devices come with immense risk for making sure employee trust and retention don’t plummet at the same rate data-gathering soars. Leaders—and their HR partners—play a vital role in ensuring that the Internet of Things doesn’t harm the Interests of People.

How Does the Internet of Things Affect Employees?

The Internet of Things is already in use to capture employee-related workplace data in several new and enhanced ways:

  • Biometric sensors track where employees are at all times, who they are interacting with, and even the tone, volume, and speech patterns of their conversations with others.
  • Wearable devices gauge employee productivity (for example, in a warehouse) based on their speed of movement, how long they remain in one place, and how often they need to retrace their steps to complete a task.
  • Location sensors can project when an employee won’t reach his or her destination in time for an important meeting and can send a notification to alert other attendees to delay the start time.
  • Fitness monitors allow companies to prompt employees to be more active and to tailor health recommendations to employee activity levels, in turn guiding choices about company-sponsored health plans.
  • “Augmented reality” apps and glasses provide employees with up-to-date information about their surroundings, guiding and recording their actions in real-time.
  • Devices attached to company-provided transportation gauge risk for the company when drivers exceed speed limits or stop at locations outside of their prescribed route.

In addition, devices already connected to the internet such as computers, tablets, and phones continue to be a prolific source of data about employee productivity and susceptibility to non-work diversions. These devices have also become “smarter” in their ability to recommend breaks for employees staring at a screen for too long or to prompt a user with topic ideas when they appear to be struggling to complete a written report.

What are the Benefits of Employee-Focused IoT?

For companies able to successfully harness a vastly expanded range and depth of data about its employees, the benefits are massive. Research has shown gains in employee productivity of 8.5 percent and of job satisfaction of 3.5 percent. Extending across an entire workforce, these effects can generate millions of dollars or euros in returns on the technology investment. These advantages can be further amplified by the use of IoT data to fuel an organization’s people analytics efforts to predict and prescribe employee behaviors. Successful, future-oriented HR analytics in turn produce their own benefits and are closely linked to an organization’s financial performance.

What are the Negative Consequences?

Ignoring the human side of the Internet of Things will have important consequences for employees and their leaders—HR is uniquely placed to know and work with leaders to manage these risks. Consider these areas of likely negative impact of poorly-designed and implemented IoT systems:

  • Resentment and ultimately disengagement stemming from a lack of privacy and control
  • Legal action – in one recent lawsuit, an employee filed suit against her former employer when she was fired after becoming frustrated with and uninstalling a tracking app
  • Increased stress levels resulting from the increased scrutiny on to-the-second actions, which in turn can lead to degraded health and loss of work time
  • Turnover and damage to the company’s brand as an employer of choice

However, as the research referenced above shows, job satisfaction can also be boosted for companies using IoT. So what factors make a difference in generating a positive employee reaction to IoT, and how should HR and leaders be influencing the effort accordingly?

7 Ways Leaders and HR Can Maximize the Payoff of IoT

Leaders and HR can shape higher-return, lower-risk use of employee-focused IoT in 7 ways:

  1. Build a foundation of trust. Obviously, employee trust is important for far more than IoT, but research has shown it’s an essential factor in whether employees react with resentment or optimism about performance monitoring systems such as IoT. HR can make sure programs are in place to develop leaders in necessary trust-building skills.
  2. Improve comfort, familiarity, and proficiency with data of all types, but specifically for IoT. Unfortunately, this is not an area of strength for many leaders, only 60 percent of whom feel highly confident leveraging technology to improve the workforce, or in fact for HR itself. This gap must be closed for leaders to confidently implement IoT with their own employees.
  3. Make sure the IoT data are right and accurate. Leaders must take time to understand what IoT data actually are and to exert influence to make sure that the right data are gathered to provide accurate information about their employees, including factoring out extraneous factors leading to misinterpretation of the data. Too often, data are gathered based on ease rather than value, and leaders must take ownership about the information gathered about their employees.
  4. Know exactly what the IoT data will (and won’t) be used for. Is the data really going to help employees become better…or is it just a way to catch them doing something wrong? Research shows that tracking information viewed as developmental is much more likely to be seen as fair and more likely to induce job satisfaction and commitment.
  5. Plan how leaders will use the data to give personalized feedback to employees. This can’t be overstated and is the factor that makes the biggest difference in how IoT is seen by employees. Simply, how is the data helping employees learn and grow? If leaders can’t make a credible case for why and how, negative effects are almost guaranteed.
  6. Arm leaders to respond with empathy. Leaders skilled in listening and responding to employees with empathy will be better prepared to quell their concerns about the collection and use of new data about their activities. HR can make sure they have the interaction skills they need.
  7. Finally, communicate in advance about the reasons and benefits of IoT from the employee’s rather than the company’s perspective—long before the first device is strapped to an employee’s wrist or the first datapoint is gathered.

Companies plunging headlong into the Internet of Things trend do so for many business reasons, yet the employee’s viewpoint is often not considered when these plans are made—those who wear or are tracked by IoT devices are an afterthought.  Strong awareness and planned skill-building stemming from an HR-leader partnership is the key to prevent IoT’s Big Data from being seen by employees as Big Brother.

Evan Sinar, Ph.D. is DDI’s Chief Scientist and director of DDI’s Center for Analytics and Behavioral Research (CABER).

Posted: 09 Dec, 2015,
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